scholarly journals Physical Activity, Sedentary Behavior, and Retirement: The Multi-Ethnic Study of Atherosclerosis

2018 ◽  
Vol 54 (6) ◽  
pp. 786-794 ◽  
Author(s):  
Sydney A. Jones ◽  
Quefeng Li ◽  
Allison E. Aiello ◽  
Angela M. O’Rand ◽  
Kelly R. Evenson
Keyword(s):  
Physical Activity ◽  
Sedentary Behavior ◽  
Ethnic Study

Abstract MP16: Reallocating Sedentary Behavior With Sleep or Physical Activity is Associated With Favorable Cardiovascular Health in the Multi-Ethnic Study of Atherosclerosis: MESA

Circulation ◽  
2020 ◽  
Vol 141 (Suppl_1) ◽  
Author(s):  
Charles German ◽  
Nour Makarem ◽  
Jason Fanning ◽  
Susan Redline ◽  
Tali Elfassy ◽  
...  
Keyword(s):  
Physical Activity ◽  
Risk Factors ◽  
Blood Pressure ◽  
Sedentary Behavior ◽  
Diastolic Blood Pressure ◽  
Cardiovascular Health ◽  
Sedentary Time ◽  
Vigorous Physical Activity ◽  
Ethnic Study ◽  
The Mean

Introduction: Sleep, sedentary behavior, and physical activity are each independently associated with cardiovascular health (CVH). However, many studies have investigated these relationships in isolation even though a change in any one given behavior will affect the time spent in the others. It is unknown how reallocating time in sedentary behavior with sleep or physical activity effects overall CVH in a diverse cohort of men and women at risk of cardiovascular disease (CVD). Hypothesis: Reallocating 30 minutes of sedentary time with sleep, light (LIPA), or moderate to vigorous physical activity (MVPA) is associated with more favorable overall CVH due to improvements in risk factors for CVD. Methods: Data for this analysis were taken from the Multi-Ethnic Study on Atherosclerosis (MESA) Sleep Ancillary Study. Eligible participants (n= 1718) wore Actiwatch accelerometers for 24 hours a day, and had at least 3 days of valid accelerometry. Time spent in sleep, sedentary behavior, LIPA, and MVPA was determined based on an established algorithm. The American Heart Association’s life simple 7 was used to represent the CVH score after excluding the physical activity component, with higher scores indicating more favorable CVH. All components were ascertained from MESA exam 5. Isotemporal substitution modeling was conducted to examine the effect of substituting 30 minutes of sedentary time for an equivalent amount of sleep, LIPA, or MVPA. Results: The mean age of participants was 68.3, 54.0% were female and 38.6% were white. The mean CVH score was 5.9 (95%CI: 5.8-6.0). On average, participants spent 499.3 minutes/day in sedentary time, 415.3 minutes/day in LIPA, 26.0 minutes/day in MVPA, and 388.2 minutes/day sleeping. Reallocating 30 minutes of sedentary time to sleep, LIPA, and MVPA was associated with a significantly higher CVH score [β(SE): 0.077(0.023), 0.039(0.017), and 0.485(0.065) respectively]. Reallocating 30 minutes of sedentary time to sleep was associated with lower BMI. Reallocating 30 minutes of sedentary time to LIPA was associated with higher diastolic blood pressure and total cholesterol, and lower BMI. Reallocating 30 minutes of sedentary time to MVPA was associated with lower systolic and diastolic blood pressure, and lower BMI. Conclusions: Our study demonstrates that sleep, LIPA, and MVPA are all positively associated with more favorable overall CVH and several key CVD risk factors. These findings underscore the importance of lifestyle modifications in improving CVH.

Comparisons of physical activity and sedentary behavior between owners and non-owners of commercial wearable devices

2021 ◽  
Vol 141 (2) ◽  
pp. 89-96
Author(s):  
Hsin-Yen Yen ◽  
Hao-Yun Huang
Keyword(s):  
Physical Activity ◽  
Sleep Quality ◽  
Sedentary Behavior ◽  
Sedentary Time ◽  
Short Form ◽  
Wearable Devices ◽  
Wearable Device ◽  
World Health ◽  
World Health Organization Quality ◽  
Quality Of Life Scale

Aims: Wearable devices are a new strategy for promoting physical activity in a free-living condition that utilizes self-monitoring, self-awareness, and self-determination. The main purpose of this study was to explore health benefits of commercial wearable devices by comparing physical activity, sedentary time, sleep quality, and other health outcomes between individuals who used and those that did not use commercial wearable devices. Methods: The research design was a cross-sectional study using an Internet survey in Taiwan. Self-administered questionnaires included the International Physical Activity Questionnaire–Short Form, Pittsburgh Sleep Quality Index, Health-Promoting Lifestyle Profile, and World Health Organization Quality-of-Life Scale. Results: In total, 781 participants were recruited, including 50% who were users of wearable devices and 50% non-users in the most recent 3 months. Primary outcomes revealed that wearable device users had significantly higher self-reported walking, moderate physical activity, and total physical activity, and significantly lower sedentary time than non-users. Wearable device users had significantly better sleep quality than non-users. Conclusion: Wearable devices inspire users’ motivation, engagement, and interest in physical activity through habit formation. Wearable devices are recommended to increase physical activity and decrease sedentary behavior for promoting good health.

scholarly journals 2020 WHO guidelines on physical activity and sedentary behavior

2021 ◽  
Author(s):  
Anthony D. Okely ◽  
Anna Kontsevaya ◽  
Johan Ng ◽  
Chalchisa Abdeta
Keyword(s):  
Physical Activity ◽  
Sedentary Behavior ◽  
Who Guidelines

scholarly journals Associations of working from home with occupational physical activity and sedentary behavior under the COVID‐19 pandemic

2021 ◽  
Vol 63 (1) ◽  
Author(s):  
Noritoshi Fukushima ◽  
Masaki Machida ◽  
Hiroyuki Kikuchi ◽  
Shiho Amagasa ◽  
Toshio Hayashi ◽  
...  
Keyword(s):  
Physical Activity ◽  
Sedentary Behavior ◽  
Occupational Physical Activity ◽  
Working From Home

scholarly journals Can Health-Promoting Schools Contribute to Better Health Behaviors? Physical Activity, Sedentary Behavior, and Dietary Habits among Israeli Adolescents

2021 ◽  
Vol 18 (3) ◽  
pp. 1183
Author(s):  
Hila Beck ◽  
Riki Tesler ◽  
Sharon Barak ◽  
Daniel Sender Moran ◽  
Adilson Marques ◽  
...  
Keyword(s):  
Physical Activity ◽  
Health Behavior ◽  
Confidence Interval ◽  
Health Behaviors ◽  
Sedentary Behavior ◽  
Dietary Habits ◽  
Group Differences ◽  
Time Behavior ◽  
Health Promoting ◽  
The Mean

Schools with health-promoting school (HPS) frameworks are actively committed to enhancing healthy lifestyles. This study explored the contribution of school participation in HPS on students’ health behaviors, namely, physical activity (PA), sedentary behavior, and dieting. Data from the 2018/2019 Health Behavior in School-aged Children study on Israeli adolescents aged 11–17 years were used. Schools were selected from a sample of HPSs and non-HPSs. Between-group differences and predictions of health behavior were analyzed. No between-group differences were observed in mean number of days/week with at least 60 min of PA (HPS: 3.84 ± 2.19 days/week, 95% confidence interval of the mean = 3.02–3.34; non-HPS: 3.93 ± 2.17 days/week, 95% confidence interval of the mean = 3.13–3.38). Most children engaged in screen time behavior for >2 h/day (HPS: 60.83%; non-HPS: 63.91%). The odds of being on a diet were higher among more active children (odds ratio [OR] = 1.20), higher socio-economic status (OR = 1.23), and female (OR = 2.29). HPS did not predict any health behavior. These findings suggest that HPSs did not contribute to health behaviors more than non-HPSs. Therefore, health-promoting activities in HPSs need to be improved in order to justify their recognition as members of the HPS network and to fulfill their mission.

scholarly journals Associations between objectively measured physical activity, sedentary behaviour and time in bed among 75+ community-dwelling Danish older adults

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Li-Tang Tsai ◽  
Eleanor Boyle ◽  
Jan C. Brønd ◽  
Gry Kock ◽  
Mathias Skjødt ◽  
...  
Keyword(s):  
Physical Activity ◽  
Older Adults ◽  
Sedentary Behavior ◽  
Sedentary Behaviour ◽  
Sleep Duration ◽  
Activity Level ◽  
Time In Bed ◽  
Objectively Measured ◽  
Objectively Measured Physical Activity ◽  
Vector Magnitude

Abstract Background Older adults are recommended to sleep 7–8 h/day. Time in bed (TIB) differs from sleep duration and includes also the time of lying in bed without sleeping. Long TIB (≥9 h) are associated with self-reported sedentary behavior, but the association between objectively measured physical activity, sedentary behavior and TIB is unknown. Methods This study was based on cross-sectional analysis of the Healthy Ageing Network of Competence (HANC Study). Physical activity and sedentary behaviour were measured by a tri-axial accelerometer (ActiGraph) placed on the dominant wrist for 7 days. Sedentary behavior was classified as < 2303 counts per minute (cpm) in vector magnitude and physical activity intensities were categorized, as 2303–4999 and ≥ 5000 cpm in vector magnitude. TIB was recorded in self-reported diaries. Participants were categorized as UTIB (usually having TIB 7–9 h/night: ≥80% of measurement days), STIB (sometimes having TIB 7–9 h/night: 20–79% of measurement days), and RTIB (rarely having TIB 7–9 h/night: < 20% of measurement days). Multinominal regression models were used to calculate the relative risk ratios (RRR) of being RTIB and STIB by daily levels of physical activity and SB, with UTIB as the reference group. The models were adjusted for age, sex, average daily nap length and physical function. Results Three hundred and fourty-one older adults (median age 81 (IQR 5), 62% women) were included with median TIB of 8 h 21 min (1 h 10 min)/day, physical activity level of 2054 (864) CPM with 64 (15) % of waking hours in sedentary behavior. Those with average CPM within the highest tertile had a lower RRR (0.33 (0.15–0.71), p = 0.005) for being RTIB compared to those within the lowest tertile of average CPM. Accumulating physical activity in intensities 2303–4999 and ≥ 5000 cpm/day did not affect the RRR of being RTIB. RRR of being RTIB among highly sedentary participants (≥10 h/day of sedentary behavior) more than tripled compared to those who were less sedentary (3.21 (1.50–6.88), p = 0.003). Conclusions For older adults, being physically active and less sedentary was associated with being in bed for 7–9 h/night for most nights (≥80%). Future longitudinal studies are warranted to explore the causal relationship sbetween physical activity and sleep duration.

scholarly journals Physical activity, sedentary behavior and risk of coronary artery disease, myocardial infarction and ischemic stroke: a two-sample Mendelian randomization study

2021 ◽  
Author(s):  
Martin Bahls ◽  
Michael F. Leitzmann ◽  
André Karch ◽  
Alexander Teumer ◽  
Marcus Dörr ◽  
...  
Keyword(s):  
Physical Activity ◽  
Myocardial Infarction ◽  
Coronary Artery Disease ◽  
Ischemic Stroke ◽  
Coronary Artery ◽  
Sedentary Behavior ◽  
Mendelian Randomization ◽  
Disease Risk ◽  
Cardiovascular Disease Risk ◽  
Artery Disease

Abstract Aims Observational evidence suggests that physical activity (PA) is inversely and sedentarism positively related with cardiovascular disease risk. We performed a two-sample Mendelian randomization (MR) analysis to examine whether genetically predicted PA and sedentary behavior are related to coronary artery disease, myocardial infarction, and ischemic stroke. Methods and results We used single nucleotide polymorphisms (SNPs) associated with self-reported moderate to vigorous PA (n = 17), accelerometer based PA (n = 7) and accelerometer fraction of accelerations > 425 milli-gravities (n = 7) as well as sedentary behavior (n = 6) in the UK Biobank as instrumental variables in a two sample MR approach to assess whether these exposures are related to coronary artery disease and myocardial infarction in the CARDIoGRAMplusC4D genome-wide association study (GWAS) or ischemic stroke in the MEGASTROKE GWAS. The study population included 42,096 cases of coronary artery disease (99,121 controls), 27,509 cases of myocardial infarction (99,121 controls), and 34,217 cases of ischemic stroke (404,630 controls). We found no associations between genetically predicted self-reported moderate to vigorous PA, accelerometer-based PA or accelerometer fraction of accelerations > 425 milli-gravities as well as sedentary behavior with coronary artery disease, myocardial infarction, and ischemic stroke. Conclusions These results do not support a causal relationship between PA and sedentary behavior with risk of coronary artery disease, myocardial infarction, and ischemic stroke. Hence, previous observational studies may have been biased. Graphic abstract

scholarly journals The Comparison of Physical Activity, Sedentary Behavior, and Mental Health between Early Menopausal Women and Age-Matched General Middle-Aged Women

2021 ◽  
Vol 18 (14) ◽  
pp. 7256
Author(s):  
Ji-Su Kim ◽  
Ju-Pil Choe ◽  
Jeong-Hui Park ◽  
Eunhye Yoo ◽  
Jung-Min Lee
Keyword(s):  
Mental Health ◽  
Physical Activity ◽  
Sedentary Behavior ◽  
Healthy Lifestyle ◽  
Multinomial Logistic Regression ◽  
Middle Aged ◽  
General Group ◽  
Menopausal Women ◽  
Global Physical Activity Questionnaire ◽  
Causes Of Mortality

The current study is to examine the differences in physical activity (PA), sedentary behavior (SB), and mental health (i.e., stress, depression, and suicidal behaviors) between early menopausal women and age-matched general middle-aged women. Among 1348 participants in South Korea, 674 participants who experienced menopause before the age of 45 were defined as the early menopausal group, and 674 women who experienced menopause from 45 years to 55 years were classified as the general group by matching age based on early menopausal women. PA, SB, and mental health were evaluated by using the Global Physical Activity Questionnaire (GPAQ). An independent t-test was used to compare the associations of PA, SB, and mental health between the two groups. To demonstrate the predictors of early menopause, variables in the study were analyzed by multinomial logistic regression. The main findings were that moderate-to-vigorous PA (MVPA) and light PA (LPA) had significant differences between the two groups, but SB had no significant differences. In mental health, only perceived stress had significant differences in this study. The moderate level of stress in the early menopausal group was twice as high as that of the general group, and the severe level of stress was even 2.6 times higher than the general group. PA plays an essential role in mitigating the causes of mortality and the risk of various chronic diseases and improving quality of life; thus, the main findings of this study could be important to provide insights on the corresponding impact between early menopausal women and PA to encourage their healthy lifestyle. Further longitudinal studies are needed to examine the mechanisms underlying the effects of PA, SB, and mental health on early menopausal women.

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